Two important questions before we begin

Two important questions before we begin

video link

• We'll be doing some introductions shortly.

• You might have some clear ideas/goals – we want to hear them

• You might not know – you are welcome, too

• Your reasons might change as the week goes along

1. Shop
2. Work

More details at http://dtkaplan.github.io/CVC/schedule2017.html

• Please bookmark this page. We will post links to materials on this page so you can access them.

Shop

In the first 2.5 days, we will present you with some tools for learning from data and give you an opportunity to give them a test drive

• introduction to R and RStudio
• data visualization
• data manipulation (tidying, cleaning, summarizing, etc.)
• reproducible workflow with RMarkdown

You get to "try things on" and "see how they fit"

Work

In the second 2.5 days, you will have a chance to prepare something (some things) of your own choosing to use

• in a class
• in a lab
• in your research
• ???

We will work with you to find and learn what you need

• collaboration is encouraged

You will be working already in Part 1

• Goal: By Wednesday lunch, everyone will have

  • tried out a number of "exercises" in R/RStudio/RMarkdown

  • learned something new and have more new things they want to learn in Part 2.

  • identified a project to work on in Part 2.

There will also be some shopping in Part 2

• we will be collecting up ideas based on your interests, needs, wishes

• some of these may be "optional" – those who are interested may join in, others may choose to keep working

Our schedule does not include any times.

• Start at 9 am end around 4:30 pm with breaks/lunch as needed.

We can take the time we need before moving on

• Be sure to ask questions and provide us feedback so we can adjust appropriately.

R is one tool for working with data, but many of the things we will talk about are more general than R and apply equally to other ways of working with data.

R's particular advantages:

• state of the art (high quality, wide scope)
  • widely used in academia and industry
• excellent data visualization
• reproducible workflow tools
• free!

1. Get into a group of 3 or 4 people.
2. Introduce yourselves.
   • be sure to mention something about what sort of project you might be interested in
3. Remember or take some notes (you will need them shortly).

Use this google doc to create a short "bio" for one of the others in your group.

• Bulleted list or paragraph – which every you prefer.
• Include a photo if possible.